本課程是 AI in Healthcare 專項課程專項課程的一部分

4.5
星
114 個評分

Tina Hernandez-Boussard 另外 +1 位授課教師

5,257 人已註冊

提供方

AI in Healthcare 專項課程斯坦福大学

課程信息

18,437 次近期查看

With artificial intelligence applications proliferating throughout the healthcare system, stakeholders are faced with both opportunities and challenges of these evolving technologies. This course explores the principles of AI deployment in healthcare and the framework used to evaluate downstream effects of AI healthcare solutions.
The Stanford University School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians.  Visit the FAQs below for important information regarding 1) Date of original release and Termination or expiration date; 2) Accreditation and Credit Designation statements; 3) Disclosure of financial relationships for every person in control of activity content.

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完成後獲得證書

100% 在線

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第 4 門課程（共 5 門）

AI in Healthcare 專項課程

初級

完成時間大約為11 小時

英語（English）

字幕：法語（French）, （歐洲人講的）葡萄牙語, 俄語（Russian）, 英語（English）, 西班牙語（Spanish）

您將學到的內容有

Principles and practical considerations for integrating AI into clinical workflows

Best practices of AI applications to promote fair and equitable healthcare solutions

Challenges of regulation of AI applications and which components of a model can be regulated

What standard evaluation metrics do and do not provide

可靈活調整截止日期

根據您的日程表重置截止日期。

可分享的證書

完成後獲得證書

100% 在線

立即開始，按照自己的計劃學習。

第 4 門課程（共 5 門）

AI in Healthcare 專項課程

初級

完成時間大約為11 小時

英語（English）

字幕：法語（French）, （歐洲人講的）葡萄牙語, 俄語（Russian）, 英語（English）, 西班牙語（Spanish）

授課教師

授課教師評分

4.55/5 （44 個評分）

Tina Hernandez-Boussard

Associate Professor

Medicine (Biomedical Informatics), of Biomedical Data Science and of Surgery

6,250 個學生

2 門課程

Mildred Cho

Professor

Department of Pediatrics Division of Medical Genetics

20,138 個學生

2 門課程

提供方

斯坦福大学

The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States.

授課大綱 - 您將從這門課程中學到什麼

週

週 1

完成時間為 1 小時

AI in Healthcare

完成時間為 1 小時

10 個視頻（總計 30 分鐘）, 2 個閱讀材料, 3 個測驗

10 個視頻

Learning Objectives1分鐘

Common Definitions1分鐘

Overview1分鐘

Why AI is needed in Healthcare4分鐘

Examples of AI in Healthcare8分鐘

Growth of AI in Healthcare2分鐘

Questions Answered by AI2分鐘

AI Output3分鐘

Think beyond area under the curve1分鐘

Recap2分鐘

2 個閱讀材料

Study Guide Module 1

Citations and Additional Readings

3 個練習

Reflection Exercise 110分鐘

Reflection Exercise 210分鐘

Knowledge Check20分鐘

週

週 2

完成時間為 2 小時

Evaluations of AI in Healthcare

完成時間為 2 小時

15 個視頻（總計 41 分鐘）, 2 個閱讀材料, 4 個測驗

15 個視頻

Learning Objectives1分鐘

Recap: Framework1分鐘

Stakeholders1分鐘

Clinical Utility1分鐘

Outcome: Action Pairing, An Overview4分鐘

Lead Time1分鐘

Type of Action3分鐘

OAP Examples3分鐘

Number Needed to Treat2分鐘

Net Benefits2分鐘

Decision Curves4分鐘

Feasibility overview4分鐘

Implementation Costs1分鐘

Clinical Evaluation and Uptake4分鐘

Summary1分鐘

2 個閱讀材料

Study Guide Module 25分鐘

Citations and Additional Readings

4 個練習

Reflection Exercise 110分鐘

Reflection Exercise 210分鐘

Reflection Exercise 310分鐘

Knowledge Check30分鐘

週

週 3

完成時間為 2 小時

AI Deployment

完成時間為 2 小時

19 個視頻（總計 47 分鐘）, 2 個閱讀材料, 5 個測驗

19 個視頻

Learning Objectives1分鐘

The Problem1分鐘

Practical Questions Prior to Deployment3分鐘

Deployment Pathway1分鐘

Design and Development3分鐘

Stakeholder Involvement2分鐘

Data Type and Sources3分鐘

Settings3分鐘

In Silico Evaluation2分鐘

Net Utility & Work Capacity2分鐘

Statistical Validity1分鐘

Care Integration, Silent Mode2分鐘

Clinical Integration, Considerations2分鐘

Technical Integration1分鐘

Deployment Modalities2分鐘

Continuous Monitoring and Maintenance2分鐘

Challenges of Deployment5分鐘

Sepsis Example1分鐘

Summary1分鐘

2 個閱讀材料

Study Guide Module 35分鐘

Citations and Additional Readings

5 個練習

Reflection Exercise 110分鐘

Reflection Exercise 210分鐘

Reflection Exercise 310分鐘

Reflection Exercise 410分鐘

Knowledge Check30分鐘

週

週 4

完成時間為 2 小時

Downstream Evaluations of AI in Healthcare: Bias and Fairness

完成時間為 2 小時

18 個視頻（總計 41 分鐘）, 2 個閱讀材料, 5 個測驗

18 個視頻

Learning Objectives2分鐘

Real World Examples of AI Bias4分鐘

Introduction - Types of Bias41

Historical Bias2分鐘

Representation Bias1分鐘

Measurement Bias1分鐘

Aggregation Bias2分鐘

Evaluation Bias1分鐘

Deployment Bias1分鐘

What is algorithmic Fairness2分鐘

Anti-classification2分鐘

Parity Classification1分鐘

Calibration2分鐘

Applying Fairness Measures2分鐘

Lack of Transparency2分鐘

Minimal Reporting Standards3分鐘

Opportunities and Challenges2分鐘

Summary2分鐘

2 個閱讀材料

Study Guide Module 45分鐘

Citations and Additional Readings

5 個練習

Reflection Exercise 110分鐘

Reflection Exercise 210分鐘

Reflection Exercise 310分鐘

Reflection Exercise 410分鐘

Knowledge Check30分鐘

審閱

4.5

31 條評論

5 stars
67.82%
4 stars
20%
3 stars
6.08%
2 stars
3.47%
1 star
2.60%

來自EVALUATIONS OF AI APPLICATIONS IN HEALTHCARE的熱門評論

由 RS 提供2021年3月5日

This is a holistic course giving all perspectives and knowledge on the different aspects of evaluating all kind of AI driven solutions in healthcare. A must do for all healthcare Managers.

由 GG 提供2020年12月12日

Thanks a lot for this great course, extremely practical, allowing to create a clear action plan for AI evaluation.

由 KS 提供2020年10月16日

Nicely Framed and Executed in a simple language so anyone can catch up earliest.

由 KN 提供2020年12月2日

More examples would have been better to understand some of the concepts.

查看所有評論

關於 AI in Healthcare 專項課程

Artificial intelligence (AI) has transformed industries around the world, and has the potential to radically alter the field of healthcare. Imagine being able to analyze data on patient visits to the clinic, medications prescribed, lab tests, and procedures performed, as well as data outside the health system -- such as social media, purchases made using credit cards, census records, Internet search activity logs that contain valuable health information, and you’ll get a sense of how AI could transform patient care and diagnoses.

In this specialization, we'll discuss the current and future applications of AI in healthcare with the goal of learning to bring AI technologies into the clinic safely and ethically. This specialization is designed for both healthcare providers and computer science professionals, offering insights to facilitate collaboration between the disciplines. CME Accreditation The Stanford University School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians. View the full CME accreditation information on the individual course FAQ page.

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讲座和作业的访问权限取决于您的注册类型。如果您以旁听模式参加课程，则可以免费查看大多数课程资料。要访问评分作业并获得证书，您需要在旁听期间或之后购买证书体验。如果看不到旁听选项：
课程可能不提供旁听选项。您可以尝试免费试用，也可以申请助学金。
课程可能会改为提供'完整课程，没有证书'。通过此选项，您可以查看所有课程材料、提交所要求的作业，以及获得最终成绩。这也意味着您将无法购买证书体验。
我订阅此专项课程后会得到什么？
您注册课程后，将有权访问专项课程中的所有课程，并且会在完成课程后获得证书。您的电子课程证书将添加到您的成就页中，您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容，可以免费旁听课程。
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是的，Coursera 可以为无法承担费用的学生提供助学金。通过点击左侧“注册”按钮下的“助学金”链接可以申请助学金。您可以根据屏幕提示完成申请，申请获批后会收到通知。您需要针对专项课程中的每一门课程完成上述步骤，包括毕业项目。了解更多。
Is this activity accredited for Continuing Medical Education (CME)?
Dates and Duration
Original Release Date: 08/10/2020
Expiration Date: 08/10/2023
Estimated Time to Complete: 9 hours and 30 minutes
CME Credits Offered: 9.50
Accreditation
The Stanford University School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians. The Stanford University School of Medicine designates this enduring material for a maximum of 9.50 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
Disclosures
The Stanford University School of Medicine adheres to ACCME Criteria, Standards and Policies regarding industry support of continuing medical education. There are no relevant financial relationships with ACCME-defined commercial interests for anyone who was in control of the content of this activity.

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Evaluations of AI Applications in Healthcare